北部湾城市群旅游规模时空格局演化与影响因素研究

Study on the Spatial-temporal Pattern Evolution and Influencing Factors of Tourism Scale in Beibu Gulf City Cluster

关键词:  旅游规模  差异性  时空格局  联系强度  北部湾城市群

Key words:  tourism scale  difference  spatial and temporal pattern  connection intensity  Beibu Gulf city cluster

摘要:

城市旅游总人次和旅游总收入是城市旅游规模的主要构成单元，分析城市旅游规模时空分布能够更全面地反映区域内城市旅游发展格局的变化特征。本研究利用北部湾城市群10个城市2010-2018年的旅游总人次和总收入的数据资料，基于熵权TOPSIS （Technique for Order Preference by Similarity to an Ideal Solution）法归一化计算旅游规模指数，通过变异系数、全局自相关莫兰指数I（Global Moran’s I）、引力模型定量分析各个城市的时空差异和空间联系强度，利用地理探测器分析空间分异影响因素。结果显示：（1）北部湾城市群旅游规模指数整体上“西强东弱”，2010年、2013年和2015年城市旅游规模在空间上呈负相关、离散分布，2018年呈正相关、趋向聚集；（2）城市群旅游规模和内部联系强度整体上明显提升，形成以南宁为核心、北海为次核心、湛江为边缘核心的基本格局；（3）2010年排名前5位的影响因子是旅行社数量、铁路客运量、第三产业比重、人均GDP和高质量旅游资源数量，2018年排名前5的影响因子是城市交通密度、水路客运量、铁路客运量、人均GDP和航空吞吐量，城市旅游影响因子交互后非线性增强或双因子增强，不同因子交互作用高于单因子作用。本研究发现北部湾城市群内部城市旅游空间差异性持续存在，但差异性逐渐缩小，城市之间相互作用、联系强度逐渐增强，影响旅游主导因素由传统依赖旅游资源、旅游配套设施条件、经济发展条件向交通通达度转变。研究结果可为优化北部湾城市群区域空间结构和旅游资源配置，构建相对合理的城市群体系提供参考。

Abstract:

The total number of tourists and tourism revenue are major components of urban tourism scale. Analyzing the spatial and temporal distribution of urban tourism scale can more comprehensively reflect the change characteristics of urban tourism development pattern in the region.This study first obtained the data of the total number of tourists and revenue from 10 cities in Beibu Culf city cluster from 2010 to 2018, and normalized to calculate the tourism scale index based on the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. The spatial-temporal differences and spatial connection intensity of each city were quantitatively analyzed by coefficient of variation, Global Moran's I and gravity model, and the influencing factors of spatial differentiation are analyzed by geographical detectors. The results show:(1) the tourism scale index of Beibu Gulf city cluster is "strong in the west and weak in the east" as a whole.In 2010, 2013 and 2015, the scale of urban tourism showed spatial negative correlation and discrete distribution, while in 2018, it showed positive correlation and tended to gather. (2) The tourism scale and internal connection intensity of city cluster had improved significantly on the whole, forming a basic pattern with Nanning as the core, Beihai as the secondary core and Zhanjiang as the marginal core. (3) In 2010 the top five influential factors were the number of travel agencies, railway passenger volume, the proportion of tertiary industry, per capita GDP and high quality tourism resources. While in 2018 the top five influence factors were urban traffic density, waterway passenger volume, railway passenger volume, per capita GDP and air passenger volume. After the interaction of urban tourism influencing factors, non-linear or double-factor was enhanced, and the interaction of different factors was higher than that of the single factor. This study found that the spatial difference of urban tourism in Beibu Gulf city cluster existed constantly, but the difference gradually narrowed, and the interaction and connection intensity between city clusters gradually increased. The dominant factors that affected tourism changed from traditional dependence on tourism resources, tourism supporting facilities and economic development conditions to traffic accessibility. The research results can provide references for optimizing the regional spatial structure and tourism resource allocation of Beibu Gulf city clusters and constructing a relatively reasonable city cluster system.